986 resultados para Electricity -- Costs -- Ontario.


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This work presents a demand side response model (DSR) which assists small electricity consumers, through an aggregator, exposed to the market price to proactively mitigate price and peak impact on the electrical system. The proposed model allows consumers to manage air-conditioning when as a function of possible price spikes. The main contribution of this research is to demonstrate how consumers can minimise the total expected cost by optimising air-conditioning to account for occurrences of a price spike in the electricity market. This model investigates how pre-cooling method can be used to minimise energy costs when there is a substantial risk of an electricity price spike. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics during hot days on weekdays in the period 2011 to 2012.

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The objective of this thesis is to find out how dominant firms in a liberalised electricity market will react when they face an increase in the level of costs due to emissions trading, and how this will effect the price of electricity. The Nordic electricity market is chosen as the setting in which to examine the question, since recent studies on the subject suggest that interaction between electricity markets and emissions trading is very much dependent on conditions specific to each market area. There is reason to believe that imperfect competition prevails in the Nordic market, thus the issue is approached through the theory of oligopolistic competition. The generation capacity available at the market, marginal cost of electricity production and seasonal levels of demand form the data based on which the dominant firms are modelled using the Cournot model of competition. The calculations are made for two levels of demand, high and low, and with several values of demand elasticity. The producers are first modelled under no carbon costs and then by adding the cost of carbon dioxide at 20€/t to those technologies subject to carbon regulation. In all cases the situation under perfect competition is determined as a comparison point for the results of the Cournot game. The results imply that the potential for market power does exist on the Nordic market, but the possibility for exercising market power depends on the demand level. In season of high demand the dominant firms may raise the price significantly above competitive levels, and the situation is aggravated when the cost of carbon dioixide is accounted for. Under low demand leves there is no difference between perfect and imperfect competition. The results are highly dependent on the price elasticity of demand.

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Transmission investments are currently needed to meet an increasing electricity demand, to address security of supply concerns, and to reach carbon-emissions targets. A key issue when assessing the benefits from an expanded grid concerns the valuation of the uncertain cash flows that result from the expansion. We propose a valuation model that accommodates both physical and economic uncertainties following the Real Options approach. It combines optimization techniques with Monte Carlo simulation. We illustrate the use of our model in a simplified, two-node grid and assess the decision whether to invest or not in a particular upgrade. The generation mix includes coal-and natural gas-fired stations that operate under carbon constraints. The underlying parameters are estimated from observed market data.

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Space heating accounts for a large portion of the world's carbon dioxide emissions. Ground Source Heat Pumps (GSHPs) are a technology which can reduce carbon emissions from heating and cooling. GSHP system performance is however highly sensitive to deviation from design values of the actual annual energy extraction/rejection rates from/to the ground. In order to prevent failure and/or performance deterioration of GSHP systems it is possible to incorporate a safety factor in the design of the GSHP by over-sizing the ground heat exchanger (GHE). A methodology to evaluate the financial risk involved in over-sizing the GHE is proposed is this paper. A probability based approach is used to evaluate the economic feasibility of a hypothetical full-size GSHP system as compared to four alternative Heating Ventilation and Air Conditioning (HVAC) system configurations. The model of the GSHP system is developed in the TRNSYS energy simulation platform and calibrated with data from an actual hybrid GSHP system installed in the Department of Earth Science, University of Oxford, UK. Results of the analysis show that potential savings from a full-size GSHP system largely depend on projected HVAC system efficiencies and gas and electricity prices. Results of the risk analysis also suggest that a full-size GSHP with auxiliary back up is potentially the most economical system configuration. © 2012 Elsevier Ltd.

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This work illustrates the influence of wind forecast errors on system costs, wind curtailment and generator dispatch in a system with high wind penetration. Realistic wind forecasts of different specified accuracy levels are created using an auto-regressive moving average model and these are then used in the creation of day-ahead unit commitment schedules. The schedules are generated for a model of the 2020 Irish electricity system with 33% wind penetration using both stochastic and deterministic approaches. Improvements in wind forecast accuracy are demonstrated to deliver: (i) clear savings in total system costs for deterministic and, to a lesser extent, stochastic scheduling; (ii) a decrease in the level of wind curtailment, with close agreement between stochastic and deterministic scheduling; and (iii) a decrease in the dispatch of open cycle gas turbine generation, evident with deterministic, and to a lesser extent, with stochastic scheduling.

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To maintain a strict balance between demand and supply in the US power systems, the Independent System Operators (ISOs) schedule power plants and determine electricity prices using a market clearing model. This model determines for each time period and power plant, the times of startup, shutdown, the amount of power production, and the provisioning of spinning and non-spinning power generation reserves, etc. Such a deterministic optimization model takes as input the characteristics of all the generating units such as their power generation installed capacity, ramp rates, minimum up and down time requirements, and marginal costs for production, as well as the forecast of intermittent energy such as wind and solar, along with the minimum reserve requirement of the whole system. This reserve requirement is determined based on the likelihood of outages on the supply side and on the levels of error forecasts in demand and intermittent generation. With increased installed capacity of intermittent renewable energy, determining the appropriate level of reserve requirements has become harder. Stochastic market clearing models have been proposed as an alternative to deterministic market clearing models. Rather than using a fixed reserve targets as an input, stochastic market clearing models take different scenarios of wind power into consideration and determine reserves schedule as output. Using a scaled version of the power generation system of PJM, a regional transmission organization (RTO) that coordinates the movement of wholesale electricity in all or parts of 13 states and the District of Columbia, and wind scenarios generated from BPA (Bonneville Power Administration) data, this paper explores a comparison of the performance between a stochastic and deterministic model in market clearing. The two models are compared in their ability to contribute to the affordability, reliability and sustainability of the electricity system, measured in terms of total operational costs, load shedding and air emissions. The process of building the models and running for tests indicate that a fair comparison is difficult to obtain due to the multi-dimensional performance metrics considered here, and the difficulty in setting up the parameters of the models in a way that does not advantage or disadvantage one modeling framework. Along these lines, this study explores the effect that model assumptions such as reserve requirements, value of lost load (VOLL) and wind spillage costs have on the comparison of the performance of stochastic vs deterministic market clearing models.

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This paper presents a detailed description of health care resource utilisation and costs of a pilot interdisciplinary health care model of palliative home care in Ontario, Canada. The descriptive evaluation entailed examining the use of services and costs of the pilot program: patient demographics, length of stay broken down by disposition (discharged, alive, death), access to services/resources, use of family physician and specialist services, and drug use. There were 434 patients included in the pilot program. Total costs were approximately CAN$2.4 million, and the cost per person amounted to approximately CAN$5586.33 with average length of stay equal to over 2 months (64.22 days). One may assume that length of stay would be influenced by the amount of service and support available. Future research might investigate whether in-home palliative home care is the most cost effective and suitable care setting for those patients requiring home care services for expected periods of time. © 2009 SAGE Publications.

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Wind energy has been identified as key to the European Union’s 2050 low carbon economy. However, as wind is a variable resource and stochastic by nature, it is difficult to plan and schedule the power system under varying wind power generation. This paper investigates the impacts of offshore wind power forecast error on the operation and management of a pool-based electricity market in 2050. The impact of the magnitude and variance of the offshore wind power forecast error on system generation costs, emission costs, dispatch-down of wind, number of start-ups and system marginal price is analysed. The main findings of this research are that the magnitude of the offshore wind power forecast error has the largest impact on system generation costs and dispatch-down of wind, but the variance of the offshore wind power forecast error has the biggest impact on emissions costs and system marginal price. Overall offshore wind power forecast error variance results in a system marginal price increase of 9.6% in 2050.

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This paper investigates the impacts of offshore wind power forecast error on the operation and management of a pool-based electricity market in 2050. The impact from offshore wind power forecast errors of up to 2000 MW on system generation costs, emission costs, dispatch-down of wind, number of start-ups and system marginal price are analysed. The main findings of this research are an increase in system marginal prices of approximately 1% for every percentage point rise in the offshore wind power forecast error regardless of the average forecast error sign. If offshore wind power generates less than forecasted (−13%) generation costs and system marginal prices increases by 10%. However, if offshore wind power generates more than forecasted (4%) the generation costs decrease yet the system marginal prices increase by 3%. The dispatch down of large quantities of wind power highlights the need for flexible interconnector capacity. From a system operator's perspective it is more beneficial when scheduling wind ahead of the trading period to forecast less wind than will be generated.

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Many cancer patients die in institutional settings despite their preference to die at home. A longitudinal, prospective cohort study was conducted to comprehensively assess the determinants of home death for patients receiving home-based palliative care. Data collected from biweekly telephone interviews with caregivers (n=302) and program databases were entered into a multivariate logistic model. Patients with high nursing costs (odds ratio [OR]: 4.3; confidence interval [CI]: 1.8-10.2) and patients with high personal support worker costs (OR: 2.3; CI: 1.1-4.5) were more likely to die at home than those with low costs. Patients who lived alone were less likely to die at home than those who cohabitated (OR: 0.4; CI: 0.2-0.8), and those with a high propensity for a home-death preference were more likely to die at home than those with a low propensity (OR: 5.8; CI: 1.1-31.3). An understanding of the predictors of place of death may contribute to the development of effective interventions that support home death.

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Discusses part of a project conducted by the authors into the logistics planning and management and costs of supplying biomass fuels to biomass-fired power stations in the UK. Defines biomass fuels and the reasons for the growth in interest in their use for electricity generation. The activities and parties involved in the biomass fuel supply chain are discussed together with the management of the chain in order to achieve smooth and consistent flow of biomass fuel to power stations. Explains the approach used to modelling the delivered costs of biomass fuels for four types of biomass fuel included in the project: forest fuel, short rotation coppice, straw and miscanthus. Comments are given on the environmental impacts of the fuel supply chains. The results indicate that straw supply systems are capable of producing the lowest delivered costs of the four fuels studied. Short rotation coppice and miscanthus, two new energy crops, are likely to have the highest delivered costs at present. This is due to the cost of growing these fuels and the financial incentives required by farmers to persuade them to grow these crops. Logistics costs (i.e. transport, storage and handling) are shown to represent a significant proportion of total delivered cost in biomass supply. Careful supply chain planning and logistics management will be of central importance to the success of the biomass industry.

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In a liberalized electricity market, the Transmission System Operator (TSO) plays a crucial role in power system operation. Among many other tasks, TSO detects congestion situations and allocates the payments of electricity transmission. This paper presents a software tool for congestion management and transmission price determination in electricity markets. The congestion management is based on a reformulated Optimal Power Flow (OPF), whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the dispatch proposed by the market operator. The transmission price computation considers the physical impact caused by the market agents in the transmission network. The final tariff includes existing system costs and also costs due to the initial congestion situation and losses costs. The paper includes a case study for the IEEE 30 bus power system.

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Congestion management of transmission power systems has achieve high relevance in competitive environments, which require an adequate approach both in technical and economic terms. This paper proposes a new methodology for congestion management and transmission tariff determination in deregulated electricity markets. The congestion management methodology is based on a reformulated optimal power flow, whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the transactions resulting from market operation. The proposed transmission tariffs consider the physical impact caused by each market agents in the transmission network. The final tariff considers existing system costs and also costs due to the initial congestion situation and losses. This paper includes a case study for the 118 bus IEEE test case.

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On February 29, 1912 The Ontario Paper Company Limited was incorporated under the leadership of Col. Robert R. McCormick. Four months later construction began in Thorold, Ontario as this location was best for the abundance of power and water and water transportation. The first machine was started at the mill on September 5, 1913. The mill was one of the most advanced of its era, using electricity instead of water power. The mill was also the first of its kind as it combined pulp and paper making instead of separating the two operations.

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Sir Adam Beck ( a London, Ontario manufacturer, Mayor and Conservative member of the provincial legislature) was a champion of municipal and provincial power ownership. Beck become the “Power Minister” and chairman of the Hydro-Electric Power Commission of Ontario which was the world’s first publicly owned utility. In 1925 the first unit of the Hydro Electric Power Commission’s Queenston Chippawa hydro-electric development on the Niagara River went into service. The station was renamed in 1950 as “Sir Adam Beck #1”. This marked the 25th anniversary of Beck’s death. This is one of 2 generating stations in Niagara Falls. There is also Adam Beck Plant #2. The Niagara generating stations supply one quarter of all power used in New York State and Ontario.Ontario Hydro has two water tunnels which traverse the entire City of Niagara Falls from the Village of Chippawa in the South to the Sir Adam Beck Hydro Electric Generating Stations in the North. Also they are in the process of building the third tunnel. In addition, Ontario Hydro has a 13.6 km open canal which traverses the entire City of Niagara Falls. Source: http://www.hydroone.com/OurCompany/Pages/OurHistory.aspx